Quads and Qwarters - an alternative to counting by months

Counting by months  is both deeply rooted and deeply flawed for many types of analysis and presentation. 

Months have varying duration and they start inconsistently on different days of the week. Any analysis of volumes by month introduces a layer of fog which can obscure the underlying patterns we are looking for.

Counting by weeks works much better. The periods are all the same length. And where the patterns of activity we are studying have an underlying shape based on days of the week, this is balanced out. A time series based on totals by week has the immediate advantage of comparing like for like.

But what do we do when we need a higher level view? Aside from the little problem of leap years, counting by years is a reasonably solid framework

In between, traditionally we would look at counting by months and by quarters. A better framework can be built up using multiples of weeks. 

So instead of 12 months of uneven length we can use 13 'quads' each of four weeks

And instead of 4 quarters of uneven length, based on months, we can use four identical length 'qwarters' each of 13 weeks

This gives balanced frameworks of comparable 'granularity' to their uneven traditional counterparts

The only big problem is deciding what to call them. Pending any better ideas, I have chosen to label the 4 week 'quads' 4w1 through to 4w13.

Similarly, I have used Qw1 through to Qw4 to match the familiar Q1 to Q4

Reference

E.Bolton. Why month-based views are unsuitable for data which exhibits weekly patterns. BI Dashboard Design. 02/02/2016